Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2067/46411
Titolo: A personalized FEM model for reproducible measurement of anti-inflammatory drugs in transdermal administration to knee
Autori: Arpaia P.
Crauso F.
Frosolone M.
Mariconda M.
Minucci, Simone 
Moccaldi N.
Data pubblicazione: 2022
A personalized model of the human knee for enhancing the inter-individual reproducibility of a measurement method for monitoring Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) after transdermal delivery is proposed. The model is based on the solution of Maxwell Equations in the electric-quasi-stationary limit via Finite Element Analysis. The dimensions of the custom geometry are estimated on the basis of knee circumference at the patella, body mass index, and sex of each individual. An optimization algorithm allows to find out the electrical parameters of each subject by experimental impedance spectroscopy data. Muscular tissues were characterized anisotropically, by extracting Cole–Cole equation parameters from experimental data acquired with twofold excitation, both transversal and parallel to tissue fibers. A sensitivity and optimization analysis aiming at reducing computational burden in model customization achieved a worst-case reconstruction error lower than 5%. The personalized knee model and the optimization algorithm were validated in vivo by an experimental campaign on thirty volunteers, 67% healthy and 33% affected by knee osteoarthritis (Kellgren–Lawrence grade ranging in [1,4]), with an average error of 3%.
URI: http://hdl.handle.net/2067/46411
ISSN: 2045-2322
DOI: https://doi.org/10.1038/s41598-021-04718-2
Diritti: Attribution-NonCommercial-NoDerivatives 4.0 International
È visualizzato nelle collezioni:A1. Articolo in rivista

File in questo documento:
File Descrizione DimensioniFormato Existing users please
s41598-021-04718-2.pdf1.63 MBAdobe PDF  Richiedi una copia
Visualizza tutti i metadati del documento

Page view(s)

controllato il 21-gen-2022

Google ScholarTM



Questo documento è distribuito in accordo con Licenza Creative Commons Creative Commons